Hi Jeremy,
Perhaps you've already figured this out. There may be a function
available in R to do this, but if not, in principle for BM it should be
fairly easy to do this "manually."
First, read your tree in:
tree<-read.tree(FILE, etc.) % put filename or paste in tree
then compute the phylogenetic VCV matrix (let's call it T):
T<-vcv.phylo(tree)
then specify your desired correlation matrix, R. If you wanted an
evolutionary correlation of 0.95 this would be:
R<-matrix(c(1,0.95,0.95,1),nrow=2,ncol=2)
then generate a matrix of random, uncorrelated values (U), e.g.:
U<-matrix(,nrow=N,ncol=2) % where N is the number of taxa
U[,1]<-rnorm(N) % (am I using this function correctly?)
U[,2]<-rnorm(N)
now give them a correlation based on R (using the Cholesky decomposite):
V<-U%*%chol(R)
now give the data correlation due to the tree:
X<-t(V)%*%chol(T)
I think that should be it. The data in X should be as data evolved by BM
on your tree with the correlation specified in your matrix, R (0.95 in
this case).
More experience users, please let me know if this is incorrect (it is
untested, so it may include errors, but I think the logic is sound).
Sincerely, Liam
Liam J. Revell
Department of Organismic and Evolutionary Biology
Harvard University
web: http://anolis.oeb.harvard.edu/~liam/
email: lrev...@fas.harvard.edu
On Mon, 18 May 2009, jeremy.beaul...@yale.edu wrote:
Hi all~
I was just wondering if there is a package or function in R that can simulate
two continuous traits with a user-specified correlation coefficient using a
known tree topology, branch lengths, and a model of Brownian motion (or even
OU, if possible)?
All the best,
Jeremy Beaulieu
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